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Data Engineering with Python

You're reading from  Data Engineering with Python

Product type Book
Published in Oct 2020
Publisher Packt
ISBN-13 9781839214189
Pages 356 pages
Edition 1st Edition
Languages
Author (1):
Paul Crickard Paul Crickard
Profile icon Paul Crickard

Table of Contents (21) Chapters

Preface Section 1: Building Data Pipelines – Extract Transform, and Load
Chapter 1: What is Data Engineering? Chapter 2: Building Our Data Engineering Infrastructure Chapter 3: Reading and Writing Files Chapter 4: Working with Databases Chapter 5: Cleaning, Transforming, and Enriching Data Chapter 6: Building a 311 Data Pipeline Section 2:Deploying Data Pipelines in Production
Chapter 7: Features of a Production Pipeline Chapter 8: Version Control with the NiFi Registry Chapter 9: Monitoring Data Pipelines Chapter 10: Deploying Data Pipelines Chapter 11: Building a Production Data Pipeline Section 3:Beyond Batch – Building Real-Time Data Pipelines
Chapter 12: Building a Kafka Cluster Chapter 13: Streaming Data with Apache Kafka Chapter 14: Data Processing with Apache Spark Chapter 15: Real-Time Edge Data with MiNiFi, Kafka, and Spark Other Books You May Enjoy Appendix

Writing and reading files in Python

The title of this section may sound strange as you are probably used to seeing it written as reading and writing, but in this section, you will write data to files first, then read it. By writing it, you will understand the structure of the data and you will know what it is you are trying to read.

To write data, you will use a library named faker. faker allows you to easily create fake data for common fields. You can generate an address by simply calling address(), or a female name using name_female(). This will simplify the creation of fake data while at the same time making it more realistic.

To install faker, you can use pip:

pip3 install faker

With faker now installed, you are ready to start writing files. The next section will start with CSV files.

Writing and reading CSVs

The most common file type you will encounter is Comma-Separated Values (CSV). A CSV is a file made up of fields separated by commas. Because commas are...

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